IGCCodonSimPAMLsummary
Load data from All.RData
rm(list=ls()) # clean up workspace
load("/Users/Xiang/GitFolders/IGCCodonSimulation/All.RData")
## try http:// if https:// URLs are not supported
#source("https://bioconductor.org/biocLite.R")
#biocLite("ggtree")
#library("ggtree")
library("ape")## Warning: package 'ape' was built under R version 3.2.3IGC.geo.list <- c(3.0, 10.0, 50.0, 100.0, 500.0)
for (IGC.geo in IGC.geo.list){
PAML.local.tree.1 <- NULL
PAML.local.tree.2 <- NULL
PAML.local.tree.3 <- NULL
tree.local.1 <- read.tree(file = paste( "/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_0/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_0_localTree_1_codeml_est.newick", sep = ""))
edge.local.1 <- tree.local.1$edge
check.1 <- TRUE
tree.local.2 <- read.tree(file = paste( "/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_0/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_0_localTree_2_codeml_est.newick", sep = ""))
edge.local.2 <- tree.local.2$edge
check.2 <- TRUE
tree.local.3 <- read.tree(file = paste( "/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_0/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_0_localTree_3_codeml_est.newick", sep = ""))
edge.local.3 <- tree.local.3$edge
check.3 <- TRUE
for (sim.num in 0:99){
newick.tree.file <- paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_", toString(sim.num),"/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_", toString(sim.num), "_localTree_1_codeml_est.newick", sep = "")
tree.local.1 <- read.tree(file = newick.tree.file)
check.1 <- check.1 & all(edge.local.1 == tree.local.1$edge)
PAML.local.tree.1 <- cbind(PAML.local.tree.1, tree.local.1$edge.length)
newick.tree.file <- paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_", toString(sim.num),"/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_", toString(sim.num), "_localTree_2_codeml_est.newick", sep = "")
tree.local.2 <- read.tree(file = newick.tree.file)
check.2 <- check.2 & all(edge.local.2 == tree.local.2$edge)
PAML.local.tree.2 <- cbind(PAML.local.tree.2, tree.local.2$edge.length)
newick.tree.file <- paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_", toString(sim.num),"/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_", toString(sim.num), "_localTree_3_codeml_est.newick", sep = "")
tree.local.3 <- read.tree(file = newick.tree.file)
check.3 <- check.3 & all(edge.local.3 == tree.local.3$edge)
PAML.local.tree.3 <- cbind(PAML.local.tree.3, tree.local.3$edge.length)
}
# Now assign rownames
node.names.1 <- c("cerevisiaeYDR418W", "paradoxusYDR418W", "mikataeYDR418W", "kudriavzeviiYDR418W",
"bayanusYDR418W", "castelliiYDR418W", "cerevisiaeYEL054C", "paradoxusYEL054C",
"mikataeYEL054C", "kudriavzeviiYEL054C", "bayanusYEL054C", "castelliiYEL054C",
"kluyveriYDR418W",
"N0", "N1", "N2", "N3", "N4", "N5",
"N6", "N7", "N8", "N9")
node.names.2 <- c("cerevisiaeYDR418W", "paradoxusYDR418W", "mikataeYDR418W", "kudriavzeviiYDR418W",
"bayanusYDR418W", "castelliiYDR418W", "cerevisiaeYEL054C", "paradoxusYEL054C",
"mikataeYEL054C", "kudriavzeviiYEL054C", "bayanusYEL054C", "castelliiYEL054C",
"kluyveriYDR418W",
"N0", "N1", "N2", "N3", "N4", "N5",
"N6", "N7", "N8", "N9")
node.names.3 <- c("cerevisiaeYDR418W", "paradoxusYDR418W", "mikataeYDR418W", "kudriavzeviiYDR418W",
"bayanusYDR418W", "castelliiYDR418W", "cerevisiaeYEL054C", "paradoxusYEL054C",
"mikataeYEL054C", "kudriavzeviiYEL054C", "bayanusYEL054C", "castelliiYEL054C",
"kluyveriYDR418W",
"N0", "N1", "N2", "N3", "N4", "N5", "N6",
"N7", "N8")
local.row.names.1 <- NULL
for (i in 1:dim(edge.local.1)[1]){
local.row.names.1 <- c(local.row.names.1, paste(node.names.1[edge.local.1[i, 1]], node.names.1[edge.local.1[i, 2]], sep = "_"))
}
local.row.names.2 <- NULL
for (i in 1:dim(edge.local.2)[1]){
local.row.names.2 <- c(local.row.names.2, paste(node.names.2[edge.local.2[i, 1]], node.names.2[edge.local.2[i, 2]], sep = "_"))
}
local.row.names.3 <- NULL
for (i in 1:dim(edge.local.3)[1]){
local.row.names.3 <- c(local.row.names.3, paste(node.names.3[edge.local.3[i, 1]], node.names.3[edge.local.3[i, 2]], sep = "_"))
}
rownames(PAML.local.tree.1) <- local.row.names.1
rownames(PAML.local.tree.2) <- local.row.names.2
rownames(PAML.local.tree.3) <- local.row.names.3
assign(paste("ape_paml_localTree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""), PAML.local.tree.1)
assign(paste("ape_paml_localTree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""), PAML.local.tree.2)
assign(paste("ape_paml_localTree_3_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""), PAML.local.tree.3)
}Now load in two representations of the correct tree topology
for (IGC.geo in IGC.geo.list){
PAML.tree.1 <- NULL
PAML.tree.2 <- NULL
tree.1 <- read.tree(file = paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_0/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_0_codeml_tree1_est.newick", sep = ""))
edge.1 <- tree.1$edge
check.1 <- TRUE
tree.2 <- read.tree(file = paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_0/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_0_codeml_tree2_est.newick", sep = ""))
edge.2 <- tree.2$edge
check.2 <- TRUE
for (sim.num in 0:99){
newick.tree.file <- paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_", toString(sim.num),"/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_", toString(sim.num), "_codeml_tree1_est.newick", sep = "")
tree.1 <- read.tree(file = newick.tree.file)
check.1 <- check.1 & all(edge.1 == tree.1$edge)
PAML.tree.1 <- cbind(PAML.tree.1, tree.1$edge.length)
newick.tree.file <- paste("/Users/Xiang/GitFolders/IGCCodonSimulation/YDR418W_YEL054C_estimatedTau/IGCgeo_", toString(IGC.geo), ".0/sim_", toString(sim.num),"/unrooted_MG94_geo_", toString(IGC.geo), ".0_Sim_", toString(sim.num), "_codeml_tree2_est.newick", sep = "")
tree.2 <- read.tree(file = newick.tree.file)
check.2 <- check.2 & all(edge.2 == tree.2$edge)
PAML.tree.2 <- cbind(PAML.tree.2, tree.2$edge.length)
}
# Now assign rownames
node.names.1 <- c("cerevisiaeYDR418W", "paradoxusYDR418W", "mikataeYDR418W", "kudriavzeviiYDR418W",
"bayanusYDR418W", "castelliiYDR418W", "cerevisiaeYEL054C", "paradoxusYEL054C",
"mikataeYEL054C", "kudriavzeviiYEL054C", "bayanusYEL054C", "castelliiYEL054C",
"kluyveriYDR418W",
"N0", "N1", "N2", "N3", "N4", "N5",
"N6", "N7", "N8", "N9", "N10")
node.names.2 <- c("kluyveriYDR418W", "castelliiYEL054C", "bayanusYEL054C", "kudriavzeviiYEL054C",
"mikataeYEL054C","cerevisiaeYEL054C", "paradoxusYEL054C", "castelliiYDR418W",
"bayanusYDR418W", "kudriavzeviiYDR418W", "mikataeYDR418W", "cerevisiaeYDR418W",
"paradoxusYDR418W",
"N0",
"N1", "N2", "N3", "N4", "N5",
"N6", "N7", "N8", "N9", "N10")
row.names.1 <- NULL
for (i in 1:dim(edge.1)[1]){
row.names.1 <- c(row.names.1, paste(node.names.1[edge.1[i, 1]], node.names.1[edge.1[i, 2]], sep = "_"))
}
row.names.2 <- NULL
for (i in 1:dim(edge.2)[1]){
row.names.2 <- c(row.names.2, paste(node.names.2[edge.2[i, 1]], node.names.2[edge.2[i, 2]], sep = "_"))
}
rownames(PAML.tree.1) <- row.names.1
rownames(PAML.tree.2) <- row.names.2
assign(paste("ape_paml_Tree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""), PAML.tree.1)
assign(paste("ape_paml_Tree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""), PAML.tree.2)
}Now, check if two parsers give same branch length estimates
for (IGC.geo in IGC.geo.list){
print(paste("IGC.geo = ", toString(IGC.geo)))
# Local trees
print(sum(abs(get(paste("ape_paml_localTree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = "")) - get(paste("PAML_estimatedTau_", toString(IGC.geo), ".0_LocalTree_1_summary", sep = ""))[rownames(get(paste("ape_paml_localTree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""))),])))
print(sum(abs(get(paste("ape_paml_localTree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = "")) - get(paste("PAML_estimatedTau_", toString(IGC.geo), ".0_LocalTree_2_summary", sep = ""))[rownames(get(paste("ape_paml_localTree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""))),])))
print(sum(abs(get(paste("ape_paml_localTree_3_geo_", toString(IGC.geo), ".0_blen_summary", sep = "")) - get(paste("PAML_estimatedTau_", toString(IGC.geo), ".0_LocalTree_3_summary", sep = ""))[rownames(get(paste("ape_paml_localTree_3_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""))),])))
# two representations of the correct tree topology
print(sum(abs(get(paste("ape_paml_Tree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = "")) - get(paste("PAML_estimatedTau_", toString(IGC.geo), ".0_1stTree_summary", sep = ""))[rownames(get(paste("ape_paml_Tree_1_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""))), ])))
print(sum(abs(get(paste("ape_paml_Tree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = "")) - get(paste("PAML_estimatedTau_", toString(IGC.geo), ".0_2ndTree_summary", sep = ""))[rownames(get(paste("ape_paml_Tree_2_geo_", toString(IGC.geo), ".0_blen_summary", sep = ""))), ])))
}## [1] "IGC.geo = 3"
## [1] 4.163336e-17
## [1] 0
## [1] 1.387779e-17
## [1] 1.387779e-17
## [1] 1.387779e-17
## [1] "IGC.geo = 10"
## [1] 3.469447e-18
## [1] 1.387779e-17
## [1] 2.428613e-17
## [1] 0
## [1] 0
## [1] "IGC.geo = 50"
## [1] 7.285839e-17
## [1] 1.387779e-17
## [1] 4.163336e-17
## [1] 1.734723e-17
## [1] 1.734723e-17
## [1] "IGC.geo = 100"
## [1] 0
## [1] 0
## [1] 3.469447e-18
## [1] 5.551115e-17
## [1] 5.551115e-17
## [1] "IGC.geo = 500"
## [1] 0
## [1] 0
## [1] 0
## [1] 0
## [1] 0Now, repeat what I did.
sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",] < 0)## [1] 52sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",] < 0)## [1] 59sum(PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",] < 0)## [1] 33hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_1_summary["ll",] < 0],
main = "lnL difference - local tree 1",
xlab = "lnL difference")
hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_2_summary["ll",] < 0],
main = "lnL difference - local tree 2",
xlab = "lnL difference")
hist((PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",])[PAML_estimatedTau_3.0_1stTree_summary["ll",] - PAML_estimatedTau_3.0_LocalTree_3_summary["ll",] < 0],
main = "lnL difference - local tree 3",
xlab = "lnL difference")
# Define function for converting
convert.summary <- function(localTree, summary, vector.names){
new.summary <- vector("numeric", length(vector.names))
names(new.summary) <- vector.names
if (localTree == 1){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- summary["N0_N5"]
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- 0.0
new.summary["N1_N2"] <- summary["N0_N1"]
new.summary["N1_castelliiYDR418W"] <- summary["N0_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N1_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N1_N2"]
new.summary["N3_N4"] <- summary["N2_N3"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N2_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N3_N4"]
new.summary["N4_mikataeYDR418W"] <- summary["N3_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N4_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N4_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N5_N6"]
new.summary["N6_castelliiYEL054C"] <- summary["N5_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N6_N7"]
new.summary["N7_bayanusYEL054C"] <- summary["N6_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N7_N8"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N7_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N8_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N8_N9"]
new.summary["N10_paradoxusYEL054C"] <- summary["N9_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N9_cerevisiaeYEL054C"]
}
else if (localTree == 2){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- 0.0
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- summary["N0_N1"]
new.summary["N1_N2"] <- summary["N1_N2"]
new.summary["N1_castelliiYDR418W"] <- summary["N1_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N2_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N2_N3"]
new.summary["N3_N4"] <- summary["N3_N4"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N3_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N4_N5"]
new.summary["N4_mikataeYDR418W"] <- summary["N4_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N5_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N5_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N0_N6"]
new.summary["N6_castelliiYEL054C"] <- summary["N0_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N6_N7"]
new.summary["N7_bayanusYEL054C"] <- summary["N6_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N7_N8"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N7_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N8_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N8_N9"]
new.summary["N10_paradoxusYEL054C"] <- summary["N9_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N9_cerevisiaeYEL054C"]
}
else if (localTree == 3){
new.summary[1:3] <- summary[1:3]
new.summary["N0_N6"] <- 0.0
new.summary["N0_kluyveriYDR418W"] <- summary["N0_kluyveriYDR418W"]
new.summary["N0_N1"] <- 0.0
new.summary["N1_N2"] <- summary["N0_N1"]
new.summary["N1_castelliiYDR418W"] <- summary["N0_castelliiYDR418W"]
new.summary["N2_bayanusYDR418W"] <- summary["N1_bayanusYDR418W"]
new.summary["N2_N3"] <- summary["N1_N2"]
new.summary["N3_N4"] <- summary["N2_N3"]
new.summary["N3_kudriavzeviiYDR418W"] <- summary["N2_kudriavzeviiYDR418W"]
new.summary["N4_N5"] <- summary["N3_N4"]
new.summary["N4_mikataeYDR418W"] <- summary["N3_mikataeYDR418W"]
new.summary["N5_paradoxusYDR418W"] <- summary["N4_paradoxusYDR418W"]
new.summary["N5_cerevisiaeYDR418W"] <- summary["N4_cerevisiaeYDR418W"]
new.summary["N6_N7"] <- summary["N0_N5"]
new.summary["N6_castelliiYEL054C"] <- summary["N0_castelliiYEL054C"]
new.summary["N7_N8"] <- summary["N5_N6"]
new.summary["N7_bayanusYEL054C"] <- summary["N5_bayanusYEL054C"]
new.summary["N8_N9"] <- summary["N6_N7"]
new.summary["N8_kudriavzeviiYEL054C"] <- summary["N6_kudriavzeviiYEL054C"]
new.summary["N9_mikataeYEL054C"] <- summary["N7_mikataeYEL054C"]
new.summary["N9_N10"] <- summary["N7_N8"]
new.summary["N10_paradoxusYEL054C"] <- summary["N8_paradoxusYEL054C"]
new.summary["N10_cerevisiaeYEL054C"] <- summary["N8_cerevisiaeYEL054C"]
}
else if (localTree == 4){
new.summary[vector.names] <- summary[vector.names]
}
return (new.summary)
}
for (IGC.geo in IGC.geo.list){
max.lnL.summary <- NULL
vector.names = rownames(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = "")))
for (sim.num in 1:100){
max.pos <- which.max(c(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_1_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_",paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_2_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_",paste(toString(IGC.geo), ".0", sep = ""), "_LocalTree_3_summary", sep = ""))["ll", sim.num],
get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = ""))["ll", sim.num]))
if (max.pos < 4){
new.summary <- convert.summary(max.pos, get(paste("PAML_estimatedTau", paste(toString(IGC.geo), ".0", sep = ""), "LocalTree", toString(max.pos), "summary", sep = "_"))[, sim.num], vector.names)
}
else{
new.summary <- get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = ""))[, sim.num]
}
max.lnL.summary <- cbind(max.lnL.summary, new.summary)
}
row.names(max.lnL.summary) <- row.names(get(paste("PAML_estimatedTau_", paste(toString(IGC.geo), ".0", sep = ""), "_1stTree_summary", sep = "")))
assign(paste("geo", paste(toString(IGC.geo), ".0", sep = ""), "PAML", "maxlnL", "summary", sep = "_"), max.lnL.summary)
}Feb 12 update
# Now check asymmetry again using best lnL estimates from 4 tree topologies
maxlnL.PAML.omega.mean <- c(mean(geo_3.0_PAML_maxlnL_summary["omega", ]), mean(geo_10.0_PAML_maxlnL_summary["omega", ]),
mean(geo_50.0_PAML_maxlnL_summary["omega", ]), mean(geo_100.0_PAML_maxlnL_summary["omega", ]),
mean(geo_500.0_PAML_maxlnL_summary["omega", ]))
maxlnL.PAML.omega.sd <- c(sd(geo_3.0_PAML_maxlnL_summary["omega", ]), sd(geo_10.0_PAML_maxlnL_summary["omega", ]),
sd(geo_50.0_PAML_maxlnL_summary["omega", ]), sd(geo_100.0_PAML_maxlnL_summary["omega", ]),
sd(geo_500.0_PAML_maxlnL_summary["omega", ]))
plot(IGC.geo.list, maxlnL.PAML.omega.mean)
abline(h = 1.0)
plot(IGC.geo.list, maxlnL.PAML.omega.sd)
maxlnL.PAML.kappa.mean <- c(mean(geo_3.0_PAML_maxlnL_summary["kappa", ]), mean(geo_10.0_PAML_maxlnL_summary["kappa", ]),
mean(geo_50.0_PAML_maxlnL_summary["kappa", ]), mean(geo_100.0_PAML_maxlnL_summary["kappa", ]),
mean(geo_500.0_PAML_maxlnL_summary["kappa", ]))
maxlnL.PAML.kappa.sd <- c(sd(geo_3.0_PAML_maxlnL_summary["kappa", ]), sd(geo_10.0_PAML_maxlnL_summary["kappa", ]),
sd(geo_50.0_PAML_maxlnL_summary["kappa", ]), sd(geo_100.0_PAML_maxlnL_summary["kappa", ]),
sd(geo_500.0_PAML_maxlnL_summary["kappa", ]))
plot(IGC.geo.list, maxlnL.PAML.kappa.mean)
abline(h = 8.4043336)
plot(IGC.geo.list, maxlnL.PAML.kappa.sd)
Now start to look at branch length estimates
Branch lengths used in simulation:
| Branch | blen |
|---|---|
| N0_N1: | 0.0197240946542 |
| N0_kluyveri | 0.215682181791 |
| N1_N2 | 0.20925129872 |
| N1_castellii | 0.171684721483 |
| N2_N3 | 0.0257112589202 |
| N2_bayanus | 0.0266075664688 |
| N3_N4 | 0.0321083243449 |
| N3_kudriavzevii | 0.0853588718458 |
| N4_N5 | 0.024947887926 |
| N4_mikatae | 0.0566627496729 |
| N5_cerevisiae | 0.0581451177847 |
| N5_paradoxus | 0.0218788166581 |
# N0_N1
IGC.N0.N1.mean.list <- c(mean(geo_3.0_summary["(N0,N1)", ]), mean(geo_10.0_summary["(N0,N1)", ]),
mean(geo_50.0_summary["(N0,N1)", ]), mean(geo_100.0_summary["(N0,N1)", ]),
mean(geo_500.0_summary["(N0,N1)", ]))
IGC.N0.N1.sd.list <- c(sd(geo_3.0_summary["(N0,N1)", ]), sd(geo_10.0_summary["(N0,N1)", ]),
sd(geo_50.0_summary["(N0,N1)", ]), sd(geo_100.0_summary["(N0,N1)", ]),
sd(geo_500.0_summary["(N0,N1)", ]))
PAML.N0.N1.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_N1", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_N1", ]))
PAML.N0.N1.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_N1", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_N1", ]))
PAML.N0.N1.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_N6", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_N6", ]))
PAML.N0.N1.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_N6", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_N6", ]))
# N0_kluyveri
IGC.N0.kluyveri.mean.list <- c(mean(geo_3.0_summary["(N0,kluyveri)", ]), mean(geo_10.0_summary["(N0,kluyveri)", ]),
mean(geo_50.0_summary["(N0,kluyveri)", ]), mean(geo_100.0_summary["(N0,kluyveri)", ]),
mean(geo_500.0_summary["(N0,kluyveri)", ]))
IGC.N0.kluyveri.sd.list <- c(sd(geo_3.0_summary["(N0,kluyveri)", ]), sd(geo_10.0_summary["(N0,kluyveri)", ]),
sd(geo_50.0_summary["(N0,kluyveri)", ]), sd(geo_100.0_summary["(N0,kluyveri)", ]),
sd(geo_500.0_summary["(N0,kluyveri)", ]))
PAML.N0.kluyveri.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]))
PAML.N0.kluyveri.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N0_kluyveriYDR418W", ] ))
# N1_N2
IGC.N1.N2.mean.list <- c(mean(geo_3.0_summary["(N1,N2)", ]), mean(geo_10.0_summary["(N1,N2)", ]),
mean(geo_50.0_summary["(N1,N2)", ]), mean(geo_100.0_summary["(N1,N2)", ]),
mean(geo_500.0_summary["(N1,N2)", ]))
IGC.N1.N2.sd.list <- c(sd(geo_3.0_summary["(N1,N2)", ]), sd(geo_10.0_summary["(N1,N2)", ]),
sd(geo_50.0_summary["(N1,N2)", ]), sd(geo_100.0_summary["(N1,N2)", ]),
sd(geo_500.0_summary["(N1,N2)", ]))
PAML.N1.N2.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_10.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_50.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_100.0_PAML_maxlnL_summary["N1_N2", ]),
mean(geo_500.0_PAML_maxlnL_summary["N1_N2", ]))
PAML.N1.N2.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_10.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_50.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_100.0_PAML_maxlnL_summary["N1_N2", ]),
sd(geo_500.0_PAML_maxlnL_summary["N1_N2", ]))
PAML.N1.N2.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_10.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_50.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_100.0_PAML_maxlnL_summary["N6_N7", ]),
mean(geo_500.0_PAML_maxlnL_summary["N6_N7", ]))
PAML.N1.N2.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_10.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_50.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_100.0_PAML_maxlnL_summary["N6_N7", ]),
sd(geo_500.0_PAML_maxlnL_summary["N6_N7", ]))
# N1_castellii
IGC.N1.castellii.mean.list <- c(mean(geo_3.0_summary["(N1,castellii)", ]), mean(geo_10.0_summary["(N1,castellii)", ]),
mean(geo_50.0_summary["(N1,castellii)", ]), mean(geo_100.0_summary["(N1,castellii)", ]),
mean(geo_500.0_summary["(N1,castellii)", ]))
IGC.N1.castellii.sd.list <- c(sd(geo_3.0_summary["(N1,castellii)", ]), sd(geo_10.0_summary["(N1,castellii)", ]),
sd(geo_50.0_summary["(N1,castellii)", ]), sd(geo_100.0_summary["(N1,castellii)", ]),
sd(geo_500.0_summary["(N1,castellii)", ]))
PAML.N1.castellii.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]))
PAML.N1.castellii.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ]))
PAML.N1.castellii.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]))
PAML.N1.castellii.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ]))
# N2_N3
IGC.N2.N3.mean.list <- c(mean(geo_3.0_summary["(N2,N3)", ]), mean(geo_10.0_summary["(N2,N3)", ]),
mean(geo_50.0_summary["(N2,N3)", ]), mean(geo_100.0_summary["(N2,N3)", ]),
mean(geo_500.0_summary["(N2,N3)", ]))
IGC.N2.N3.sd.list <- c(sd(geo_3.0_summary["(N2,N3)", ]), sd(geo_10.0_summary["(N2,N3)", ]),
sd(geo_50.0_summary["(N2,N3)", ]), sd(geo_100.0_summary["(N2,N3)", ]),
sd(geo_500.0_summary["(N2,N3)", ]))
PAML.N2.N3.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_10.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_50.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_100.0_PAML_maxlnL_summary["N2_N3", ]),
mean(geo_500.0_PAML_maxlnL_summary["N2_N3", ]))
PAML.N2.N3.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_10.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_50.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_100.0_PAML_maxlnL_summary["N2_N3", ]),
sd(geo_500.0_PAML_maxlnL_summary["N2_N3", ]))
PAML.N2.N3.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_10.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_50.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_100.0_PAML_maxlnL_summary["N7_N8", ]),
mean(geo_500.0_PAML_maxlnL_summary["N7_N8", ]))
PAML.N2.N3.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_10.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_50.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_100.0_PAML_maxlnL_summary["N7_N8", ]),
sd(geo_500.0_PAML_maxlnL_summary["N7_N8", ]))
# N2_bayanus
IGC.N2.bayanus.mean.list <- c(mean(geo_3.0_summary["(N2,bayanus)", ]), mean(geo_10.0_summary["(N2,bayanus)", ]),
mean(geo_50.0_summary["(N2,bayanus)", ]), mean(geo_100.0_summary["(N2,bayanus)", ]),
mean(geo_500.0_summary["(N2,bayanus)", ]))
IGC.N2.bayanus.sd.list <- c(sd(geo_3.0_summary["(N2,bayanus)", ]), sd(geo_10.0_summary["(N2,bayanus)", ]),
sd(geo_50.0_summary["(N2,bayanus)", ]), sd(geo_100.0_summary["(N2,bayanus)", ]),
sd(geo_500.0_summary["(N2,bayanus)", ]))
PAML.N2.bayanus.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]))
PAML.N2.bayanus.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ]))
PAML.N2.bayanus.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]))
PAML.N2.bayanus.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ]))
# N3_N4
IGC.N3.N4.mean.list <- c(mean(geo_3.0_summary["(N3,N4)", ]), mean(geo_10.0_summary["(N3,N4)", ]),
mean(geo_50.0_summary["(N3,N4)", ]), mean(geo_100.0_summary["(N3,N4)", ]),
mean(geo_500.0_summary["(N3,N4)", ]))
IGC.N3.N4.sd.list <- c(sd(geo_3.0_summary["(N3,N4)", ]), sd(geo_10.0_summary["(N3,N4)", ]),
sd(geo_50.0_summary["(N3,N4)", ]), sd(geo_100.0_summary["(N3,N4)", ]),
sd(geo_500.0_summary["(N3,N4)", ]))
PAML.N3.N4.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_10.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_50.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_100.0_PAML_maxlnL_summary["N3_N4", ]),
mean(geo_500.0_PAML_maxlnL_summary["N3_N4", ]))
PAML.N3.N4.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_10.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_50.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_100.0_PAML_maxlnL_summary["N3_N4", ]),
sd(geo_500.0_PAML_maxlnL_summary["N3_N4", ]))
PAML.N3.N4.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_10.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_50.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_100.0_PAML_maxlnL_summary["N8_N9", ]),
mean(geo_500.0_PAML_maxlnL_summary["N8_N9", ]))
PAML.N3.N4.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_10.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_50.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_100.0_PAML_maxlnL_summary["N8_N9", ]),
sd(geo_500.0_PAML_maxlnL_summary["N8_N9", ]))
# N3_kudriavzevii
IGC.N3.kudriavzevii.mean.list <- c(mean(geo_3.0_summary["(N3,kudriavzevii)", ]), mean(geo_10.0_summary["(N3,kudriavzevii)", ]),
mean(geo_50.0_summary["(N3,kudriavzevii)", ]), mean(geo_100.0_summary["(N3,kudriavzevii)", ]),
mean(geo_500.0_summary["(N3,kudriavzevii)", ]))
IGC.N3.kudriavzevii.sd.list <- c(sd(geo_3.0_summary["(N3,kudriavzevii)", ]), sd(geo_10.0_summary["(N3,kudriavzevii)", ]),
sd(geo_50.0_summary["(N3,kudriavzevii)", ]), sd(geo_100.0_summary["(N3,kudriavzevii)", ]),
sd(geo_500.0_summary["(N3,kudriavzevii)", ]))
PAML.N3.kudriavzevii.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]))
PAML.N3.kudriavzevii.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ]))
PAML.N3.kudriavzevii.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]))
PAML.N3.kudriavzevii.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ]))
# N4_N5
IGC.N4.N5.mean.list <- c(mean(geo_3.0_summary["(N4,N5)", ]), mean(geo_10.0_summary["(N4,N5)", ]),
mean(geo_50.0_summary["(N4,N5)", ]), mean(geo_100.0_summary["(N4,N5)", ]),
mean(geo_500.0_summary["(N4,N5)", ]))
IGC.N4.N5.sd.list <- c(sd(geo_3.0_summary["(N4,N5)", ]), sd(geo_10.0_summary["(N4,N5)", ]),
sd(geo_50.0_summary["(N4,N5)", ]), sd(geo_100.0_summary["(N4,N5)", ]),
sd(geo_500.0_summary["(N4,N5)", ]))
PAML.N4.N5.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_10.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_50.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_100.0_PAML_maxlnL_summary["N4_N5", ]),
mean(geo_500.0_PAML_maxlnL_summary["N4_N5", ]))
PAML.N4.N5.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_10.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_50.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_100.0_PAML_maxlnL_summary["N4_N5", ]),
sd(geo_500.0_PAML_maxlnL_summary["N4_N5", ]))
PAML.N4.N5.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_10.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_50.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_100.0_PAML_maxlnL_summary["N9_N10", ]),
mean(geo_500.0_PAML_maxlnL_summary["N9_N10", ]))
PAML.N4.N5.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_10.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_50.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_100.0_PAML_maxlnL_summary["N9_N10", ]),
sd(geo_500.0_PAML_maxlnL_summary["N9_N10", ]))
# N4_mikatae
IGC.N4.mikatae.mean.list <- c(mean(geo_3.0_summary["(N4,mikatae)", ]), mean(geo_10.0_summary["(N4,mikatae)", ]),
mean(geo_50.0_summary["(N4,mikatae)", ]), mean(geo_100.0_summary["(N4,mikatae)", ]),
mean(geo_500.0_summary["(N4,mikatae)", ]))
IGC.N4.mikatae.sd.list <- c(sd(geo_3.0_summary["(N4,mikatae)", ]), sd(geo_10.0_summary["(N4,mikatae)", ]),
sd(geo_50.0_summary["(N4,mikatae)", ]), sd(geo_100.0_summary["(N4,mikatae)", ]),
sd(geo_500.0_summary["(N4,mikatae)", ]))
PAML.N4.mikatae.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]))
PAML.N4.mikatae.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ]))
PAML.N4.mikatae.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]))
PAML.N4.mikatae.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ]))
# N5_cerevisiae
IGC.N5.cerevisiae.mean.list <- c(mean(geo_3.0_summary["(N5,cerevisiae)", ]), mean(geo_10.0_summary["(N5,cerevisiae)", ]),
mean(geo_50.0_summary["(N5,cerevisiae)", ]), mean(geo_100.0_summary["(N5,cerevisiae)", ]),
mean(geo_500.0_summary["(N5,cerevisiae)", ]))
IGC.N5.cerevisiae.sd.list <- c(sd(geo_3.0_summary["(N5,cerevisiae)", ]), sd(geo_10.0_summary["(N5,cerevisiae)", ]),
sd(geo_50.0_summary["(N5,cerevisiae)", ]), sd(geo_100.0_summary["(N5,cerevisiae)", ]),
sd(geo_500.0_summary["(N5,cerevisiae)", ]))
PAML.N5.cerevisiae.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]))
PAML.N5.cerevisiae.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ]))
PAML.N5.cerevisiae.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]))
PAML.N5.cerevisiae.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ]))
# N5_paradoxus
IGC.N5.paradoxus.mean.list <- c(mean(geo_3.0_summary["(N5,paradoxus)", ]), mean(geo_10.0_summary["(N5,paradoxus)", ]),
mean(geo_50.0_summary["(N5,paradoxus)", ]), mean(geo_100.0_summary["(N5,paradoxus)", ]),
mean(geo_500.0_summary["(N5,paradoxus)", ]))
IGC.N5.paradoxus.sd.list <- c(sd(geo_3.0_summary["(N5,paradoxus)", ]), sd(geo_10.0_summary["(N5,paradoxus)", ]),
sd(geo_50.0_summary["(N5,paradoxus)", ]), sd(geo_100.0_summary["(N5,paradoxus)", ]),
sd(geo_500.0_summary["(N5,paradoxus)", ]))
PAML.N5.paradoxus.maxlnL.paralog1.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
mean(geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]))
PAML.N5.paradoxus.maxlnL.paralog1.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]),
sd(geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ]))
PAML.N5.paradoxus.maxlnL.paralog2.mean.list <- c(mean(geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
mean(geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]))
PAML.N5.paradoxus.maxlnL.paralog2.sd.list <- c(sd(geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]),
sd(geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ]))Now plot same branch length estimates from each paralog in paml results and posterior branch length from IGC + MG94 model
# N0_N1
matplot(IGC.geo.list, cbind(PAML.N0.N1.maxlnL.paralog1.mean.list, PAML.N0.N1.maxlnL.paralog2.mean.list, mean.post.N0.N1.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N0.N1 estimate")
abline(h = 0.0197240946542)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N0.N1.maxlnL.paralog1.sd.list, PAML.N0.N1.maxlnL.paralog2.sd.list, sd.post.N0.N1.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N0.N1 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N0_kluyveri
matplot(IGC.geo.list, cbind(PAML.N0.kluyveri.maxlnL.paralog1.mean.list, mean.post.N0.kluyveri.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N0.kluyveri estimate")
abline(h = 0.215682181791)
legend("right", legend = c("paralog1", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N0.kluyveri.maxlnL.paralog1.sd.list, sd.post.N0.kluyveri.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N0.kluyveri estimate")
legend("right", legend = c("paralog1", "posterior IGC"), col = 1:3, pch = 1)
# N1_N2
matplot(IGC.geo.list, cbind(PAML.N1.N2.maxlnL.paralog1.mean.list, PAML.N1.N2.maxlnL.paralog2.mean.list, mean.post.N1.N2.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N1.N2 estimate")
abline(h = 0.20925129872)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N1.N2.maxlnL.paralog1.sd.list, PAML.N1.N2.maxlnL.paralog2.sd.list, sd.post.N1.N2.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N1.N2 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N1_castellii
matplot(IGC.geo.list, cbind(PAML.N1.castellii.maxlnL.paralog1.mean.list, PAML.N1.castellii.maxlnL.paralog2.mean.list, mean.post.N1.castellii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N1.castellii estimate")
abline(h = 0.171684721483)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N1.castellii.maxlnL.paralog1.sd.list, PAML.N1.castellii.maxlnL.paralog2.sd.list, sd.post.N1.castellii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N1.castellii estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N2_N3
matplot(IGC.geo.list, cbind(PAML.N2.N3.maxlnL.paralog1.mean.list, PAML.N2.N3.maxlnL.paralog2.mean.list, mean.post.N2.N3.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N2.N3 estimate")
abline(h = 0.0257112589202)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N2.N3.maxlnL.paralog1.sd.list, PAML.N2.N3.maxlnL.paralog2.sd.list, sd.post.N2.N3.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N2.N3 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N2_bayanus
matplot(IGC.geo.list, cbind(PAML.N2.bayanus.maxlnL.paralog1.mean.list, PAML.N2.bayanus.maxlnL.paralog2.mean.list, mean.post.N2.bayanus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N2.bayanus estimate")
abline(h = 0.0266075664688)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N2.bayanus.maxlnL.paralog1.sd.list, PAML.N2.bayanus.maxlnL.paralog2.sd.list, sd.post.N2.bayanus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N2.bayanus estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N3_N4
matplot(IGC.geo.list, cbind(PAML.N3.N4.maxlnL.paralog1.mean.list, PAML.N3.N4.maxlnL.paralog2.mean.list, mean.post.N3.N4.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N3.N4 estimate")
abline(h = 0.0321083243449)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N3.N4.maxlnL.paralog1.sd.list, PAML.N3.N4.maxlnL.paralog2.sd.list, sd.post.N3.N4.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N3.N4 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N3_kudriavzevii
matplot(IGC.geo.list, cbind(PAML.N3.kudriavzevii.maxlnL.paralog1.mean.list, PAML.N3.kudriavzevii.maxlnL.paralog2.mean.list, mean.post.N3.kudriavzevii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N3.kudriavzevii estimate")
abline(h = 0.0853588718458)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N3.kudriavzevii.maxlnL.paralog1.sd.list, PAML.N3.kudriavzevii.maxlnL.paralog2.sd.list, sd.post.N3.kudriavzevii.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N3.kudriavzevii estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_N5
matplot(IGC.geo.list, cbind(PAML.N4.N5.maxlnL.paralog1.mean.list, PAML.N4.N5.maxlnL.paralog2.mean.list, mean.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.N5 estimate")
abline(h = 0.024947887926)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.N5.maxlnL.paralog1.sd.list, PAML.N4.N5.maxlnL.paralog2.sd.list, sd.post.N4.N5.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.N5 estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N4_mikatae
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.maxlnL.paralog1.mean.list, PAML.N4.mikatae.maxlnL.paralog2.mean.list, mean.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N4.mikatae estimate")
abline(h = 0.0566627496729)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N4.mikatae.maxlnL.paralog1.sd.list, PAML.N4.mikatae.maxlnL.paralog2.sd.list, sd.post.N4.mikatae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N4.mikatae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N5_cerevisiae
matplot(IGC.geo.list, cbind(PAML.N5.cerevisiae.maxlnL.paralog1.mean.list, PAML.N5.cerevisiae.maxlnL.paralog2.mean.list, mean.post.N5.cerevisiae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N5.cerevisiae estimate")
abline(h = 0.0581451177847)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N5.cerevisiae.maxlnL.paralog1.sd.list, PAML.N5.cerevisiae.maxlnL.paralog2.sd.list, sd.post.N5.cerevisiae.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N5.cerevisiae estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
# N5_paradoxus
matplot(IGC.geo.list, cbind(PAML.N5.paradoxus.maxlnL.paralog1.mean.list, PAML.N5.paradoxus.maxlnL.paralog2.mean.list, mean.post.N5.paradoxus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "mean N5.paradoxus estimate")
abline(h = 0.0218788166581)
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
matplot(IGC.geo.list, cbind(PAML.N5.paradoxus.maxlnL.paralog1.sd.list, PAML.N5.paradoxus.maxlnL.paralog2.sd.list, sd.post.N5.paradoxus.list),
type = c("p"), pch = 1, col = 1:3, ylab = "sd N5.paradoxus estimate")
legend("right", legend = c("paralog1", "paralog2", "posterior IGC"), col = 1:3, pch = 1)
Now start to check branches ratio of subtree branches of paralog 1 over paralog 2 ratios
Exclude all datasets that have the edge being examined estimated to 0.
# IGC.geo = 3.0
# N0_N1
data.sets <- geo_3.0_PAML_maxlnL_summary["N0_N1", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N0_N6", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N0_N1", data.sets] / geo_3.0_PAML_maxlnL_summary["N0_N6", data.sets]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 1.075242## [1] 1.23982# N1_N2
data.sets <- geo_3.0_PAML_maxlnL_summary["N1_N2", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N6_N7", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N1_N2", data.sets] / geo_3.0_PAML_maxlnL_summary["N6_N7", data.sets]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.009263## [1] 0.2219269# N1_castellii
data.sets <- geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N1_castelliiYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N6_castelliiYEL054C", data.sets]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.010219## [1] 0.2422179# N2_N3
data.sets <- geo_3.0_PAML_maxlnL_summary["N2_N3", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N7_N8", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N2_N3", data.sets] / geo_3.0_PAML_maxlnL_summary["N7_N8", data.sets]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1.619278## [1] 3.554209# N2_bayanus
data.sets <- geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N2_bayanusYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N7_bayanusYEL054C", data.sets]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.135671## [1] 0.6685051# N3_N4
data.sets <- geo_3.0_PAML_maxlnL_summary["N3_N4", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N8_N9", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N3_N4", data.sets] / geo_3.0_PAML_maxlnL_summary["N8_N9", data.sets]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 1.5158## [1] 1.813812# N3_kudriavzevii
data.sets <- geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", data.sets]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.039909## [1] 0.3290103# N4_N5
data.sets <- geo_3.0_PAML_maxlnL_summary["N4_N5", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N9_N10", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N4_N5", data.sets] / geo_3.0_PAML_maxlnL_summary["N9_N10", data.sets]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.325159## [1] 1.523095# N4_mikatae
data.sets <- geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N4_mikataeYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N9_mikataeYEL054C", data.sets]
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.069616## [1] 0.4854722# N5_paradoxus
data.sets <- geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.390994## [1] 1.533848# N5_cerevisiae
data.sets <- geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ] > 5e-6 & geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ] > 5e-6
target <- geo_3.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", data.sets] / geo_3.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.041588## [1] 0.5020033# IGC.geo = 10.0
# N0_N1
data.sets <- geo_10.0_PAML_maxlnL_summary["N0_N1", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N0_N6", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N0_N1", data.sets] / geo_10.0_PAML_maxlnL_summary["N0_N6", data.sets]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 3.056869## [1] 6.807273# N1_N2
data.sets <- geo_10.0_PAML_maxlnL_summary["N1_N2", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N6_N7", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N1_N2", data.sets] / geo_10.0_PAML_maxlnL_summary["N6_N7", data.sets]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.071099## [1] 0.281689# N1_castellii
data.sets <- geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N1_castelliiYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N6_castelliiYEL054C", data.sets]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.025922## [1] 0.3345357# N2_N3
data.sets <- geo_10.0_PAML_maxlnL_summary["N2_N3", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N7_N8", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N2_N3", data.sets] / geo_10.0_PAML_maxlnL_summary["N7_N8", data.sets]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1.594332## [1] 2.071201# N2_bayanus
data.sets <- geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N2_bayanusYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N7_bayanusYEL054C", data.sets]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.221004## [1] 0.8686379# N3_N4
data.sets <- geo_10.0_PAML_maxlnL_summary["N3_N4", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N8_N9", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N3_N4", data.sets] / geo_10.0_PAML_maxlnL_summary["N8_N9", data.sets]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 1.538383## [1] 1.689708# N3_kudriavzevii
data.sets <- geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", data.sets]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.1444## [1] 0.4797684# N4_N5
data.sets <- geo_10.0_PAML_maxlnL_summary["N4_N5", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N9_N10", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N4_N5", data.sets] / geo_10.0_PAML_maxlnL_summary["N9_N10", data.sets]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.552732## [1] 1.281585# N4_mikatae
data.sets <- geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N4_mikataeYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N9_mikataeYEL054C", data.sets]
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.176683## [1] 0.6810652# N5_paradoxus
data.sets <- geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.317316## [1] 1.108468# N5_cerevisiae
data.sets <- geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ] > 5e-6 & geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ] > 5e-6
target <- geo_10.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", data.sets] / geo_10.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.040703## [1] 0.5688226# IGC.geo = 50.0
# N0_N1
data.sets <- geo_50.0_PAML_maxlnL_summary["N0_N1", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N0_N6", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N0_N1", data.sets] / geo_50.0_PAML_maxlnL_summary["N0_N6", data.sets]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 2.915549## [1] 5.761826# N1_N2
data.sets <- geo_50.0_PAML_maxlnL_summary["N1_N2", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N6_N7", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N1_N2", data.sets] / geo_50.0_PAML_maxlnL_summary["N6_N7", data.sets]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.073098## [1] 0.2957777# N1_castellii
data.sets <- geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N1_castelliiYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N6_castelliiYEL054C", data.sets]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.020655## [1] 0.2728165# N2_N3
data.sets <- geo_50.0_PAML_maxlnL_summary["N2_N3", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N7_N8", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N2_N3", data.sets] / geo_50.0_PAML_maxlnL_summary["N7_N8", data.sets]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1.423512## [1] 1.585746# N2_bayanus
data.sets <- geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N2_bayanusYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N7_bayanusYEL054C", data.sets]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.474417## [1] 1.93857# N3_N4
data.sets <- geo_50.0_PAML_maxlnL_summary["N3_N4", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N8_N9", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N3_N4", data.sets] / geo_50.0_PAML_maxlnL_summary["N8_N9", data.sets]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 1.589521## [1] 2.668995# N3_kudriavzevii
data.sets <- geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", data.sets]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.166183## [1] 0.7123554# N4_N5
data.sets <- geo_50.0_PAML_maxlnL_summary["N4_N5", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N9_N10", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N4_N5", data.sets] / geo_50.0_PAML_maxlnL_summary["N9_N10", data.sets]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.718912## [1] 1.740456# N4_mikatae
data.sets <- geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N4_mikataeYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N9_mikataeYEL054C", data.sets]
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.273516## [1] 1.358326# N5_paradoxus
data.sets <- geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.800851## [1] 1.848066# N5_cerevisiae
data.sets <- geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ] > 5e-6 & geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ] > 5e-6
target <- geo_50.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", data.sets] / geo_50.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.336026## [1] 0.9247276# IGC.geo = 100.0
# N0_N1
data.sets <- geo_100.0_PAML_maxlnL_summary["N0_N1", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N0_N6", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N0_N1", data.sets] / geo_100.0_PAML_maxlnL_summary["N0_N6", data.sets]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 1.316577## [1] 1.297619# N1_N2
data.sets <- geo_100.0_PAML_maxlnL_summary["N1_N2", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N6_N7", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N1_N2", data.sets] / geo_100.0_PAML_maxlnL_summary["N6_N7", data.sets]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.049548## [1] 0.3781566# N1_castellii
data.sets <- geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N1_castelliiYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N6_castelliiYEL054C", data.sets]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.032278## [1] 0.2838798# N2_N3
data.sets <- geo_100.0_PAML_maxlnL_summary["N2_N3", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N7_N8", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N2_N3", data.sets] / geo_100.0_PAML_maxlnL_summary["N7_N8", data.sets]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 1.606316## [1] 2.167851# N2_bayanus
data.sets <- geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N2_bayanusYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N7_bayanusYEL054C", data.sets]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.386256## [1] 1.510951# N3_N4
data.sets <- geo_100.0_PAML_maxlnL_summary["N3_N4", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N8_N9", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N3_N4", data.sets] / geo_100.0_PAML_maxlnL_summary["N8_N9", data.sets]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 2.141715## [1] 3.770138# N3_kudriavzevii
data.sets <- geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", data.sets]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.237804## [1] 0.973864# N4_N5
data.sets <- geo_100.0_PAML_maxlnL_summary["N4_N5", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N9_N10", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N4_N5", data.sets] / geo_100.0_PAML_maxlnL_summary["N9_N10", data.sets]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 1.746868## [1] 3.097506# N4_mikatae
data.sets <- geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N4_mikataeYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N9_mikataeYEL054C", data.sets]
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.541734## [1] 1.428149# N5_paradoxus
data.sets <- geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.870935## [1] 2.207526# N5_cerevisiae
data.sets <- geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ] > 5e-6 & geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ] > 5e-6
target <- geo_100.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", data.sets] / geo_100.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.472391## [1] 1.872967# IGC.geo = 500.0
# N0_N1
data.sets <- geo_500.0_PAML_maxlnL_summary["N0_N1", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N0_N6", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N0_N1", data.sets] / geo_500.0_PAML_maxlnL_summary["N0_N6", data.sets]
hist(target, main = "N0_N1"); mean(target); sd(target)
## [1] 2.952246## [1] 5.205804# N1_N2
data.sets <- geo_500.0_PAML_maxlnL_summary["N1_N2", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N6_N7", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N1_N2", data.sets] / geo_500.0_PAML_maxlnL_summary["N6_N7", data.sets]
hist(target, main = "N1_N2"); mean(target); sd(target)
## [1] 1.335806## [1] 1.572806# N1_castellii
data.sets <- geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N1_castelliiYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N6_castelliiYEL054C", data.sets]
hist(target, main = "N1_castellii"); mean(target); sd(target)
## [1] 1.066837## [1] 0.2984748# N2_N3
data.sets <- geo_500.0_PAML_maxlnL_summary["N2_N3", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N7_N8", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N2_N3", data.sets] / geo_500.0_PAML_maxlnL_summary["N7_N8", data.sets]
hist(target, main = "N2_N3"); mean(target); sd(target)
## [1] 2.244443## [1] 4.21793# N2_bayanus
data.sets <- geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N2_bayanusYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N7_bayanusYEL054C", data.sets]
hist(target, main = "N2_bayanus"); mean(target); sd(target)
## [1] 1.73352## [1] 1.956942# N3_N4
data.sets <- geo_500.0_PAML_maxlnL_summary["N3_N4", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N8_N9", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N3_N4", data.sets] / geo_500.0_PAML_maxlnL_summary["N8_N9", data.sets]
hist(target, main = "N3_N4"); mean(target); sd(target)
## [1] 2.969819## [1] 8.918969# N3_kudriavzevii
data.sets <- geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N3_kudriavzeviiYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N8_kudriavzeviiYEL054C", data.sets]
hist(target, main = "N3_kudriavzevii"); mean(target); sd(target)
## [1] 1.324403## [1] 1.228942# N4_N5
data.sets <- geo_500.0_PAML_maxlnL_summary["N4_N5", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N9_N10", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N4_N5", data.sets] / geo_500.0_PAML_maxlnL_summary["N9_N10", data.sets]
hist(target, main = "N4_N5"); mean(target); sd(target)
## [1] 5.654271## [1] 23.94954# N4_mikatae
data.sets <- geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N4_mikataeYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N9_mikataeYEL054C", data.sets]
hist(target, main = "N4_mikatae"); mean(target); sd(target)
## [1] 1.48522## [1] 1.834249# N5_paradoxus
data.sets <- geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N5_paradoxusYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N10_paradoxusYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_paradoxus"); mean(target); sd(target)
## [1] 1.815569## [1] 3.400141# N5_cerevisiae
data.sets <- geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", ] > 5e-6 & geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", ] > 5e-6
target <- geo_500.0_PAML_maxlnL_summary["N5_cerevisiaeYDR418W", data.sets] / geo_500.0_PAML_maxlnL_summary["N10_cerevisiaeYEL054C", data.sets] # paralog 1 / paralog 2
hist(target, main = "N5_cerevisiae"); mean(target); sd(target)
## [1] 1.352677## [1] 1.520317